ArticleeLife2021
The neural basis of intelligence in fine-grained cortical topographies.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Brain Mechanisms of Lexicality in Bilingual Emotion Processing.bioRxiv : the preprint server for biology · 2026Article
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- Representations converge as brain maps diverge along the cortical hierarchy.bioRxiv : the preprint server for biology · 2026Article
- Cortical functional hierarchy disruption following subcortical stroke.BMC medicine · 2026Article
- Dense Phenotyping of Human Brain Network Organization Using Precision fMRI.Annual review of psychology · 2026Review
- Individual differences shape conceptual representation in the brain.bioRxiv : the preprint server for biology · 2025Article
- Wired Differently? Brain Temporal Complexity and Intelligence in Autism Spectrum Disorder.Brain sciences · 2025Article
- Cortical representational geometry of diverse tasks reveals subject-specific and subject-invariant cognitive structures.Communications biology · 2025Article
- Manifold Learning Uncovers Nonlinear Interactions Between the Adolescent Brain and Environment That Predict Emotional and Behavioral Problems.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
- Using precision approaches to improve brain-behavior prediction.Trends in cognitive sciences · 2025Review
- Spurious correlations in surface-based functional brain imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Choosing explanation over performance: Insights from machine learning-based prediction of human intelligence from brain connectivity.PNAS nexus · 2024Article
- Aberrant dynamic functional network connectivity in patients with diffuse axonal injury.Scientific reports · 2024Article
- Individual cognitive traits can be predicted from task-based dynamic functional connectivity with a deep convolutional-recurrent model.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- A cortical surface template for human neuroscience.Nature methods · 2024Article
- Effects of connectivity hyperalignment (CHA) on estimated brain network properties: from coarse-scale to fine-scale.bioRxiv : the preprint server for biology · 2024Article
- Manifold learning uncovers nonlinear interactions between the adolescent brain and environment that predict emotional and behavioral problems.bioRxiv : the preprint server for biology · 2024Article
- Pre-acquired Functional Connectivity Predicts Choice Inconsistency.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Prediction of cognitive performance differences in older age from multimodal neuroimaging data.GeroScience · 2024Article
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Authors and funding
3 authors.
Funding
Abstract
Intelligent thought is the product of efficient neural information processing, which is embedded in fine-grained, topographically organized population responses and supported by fine-grained patterns of connectivity among cortical fields. Previous work on the neural basis of intelligence, however, has focused on coarse-grained features of brain anatomy and function because cortical topographies are highly idiosyncratic at a finer scale, obscuring individual differences in fine-grained connectivity patterns. We used a computational algorithm, hyperalignment, to resolve these topographic idiosyncrasies and found that predictions of general intelligence based on fine-grained (vertex-by-vertex) connectivity patterns were markedly stronger than predictions based on coarse-grained (region-by-region) patterns. Intelligence was best predicted by fine-grained connectivity in the default and frontoparietal cortical systems, both of which are associated with self-generated thought. Previous work overlooked fine-grained architecture because existing methods could not resolve idiosyncratic topographies, preventing investigation where the keys to the neural basis of intelligence are more likely to be found.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.